code: def test_standardize_channels(in_channels: int, out_channels: int):
      opts = get_config()
      setattr(
          opts, "audio_augmentation.standardize_channels.enable", True
      )
      setattr(
          opts,
          "audio_augmentation.standardize_channels.num_channels",
          out_channels,
      )
  
      N, T = 2, 5
      data = {"samples": {"audio": torch.rand(N, T, in_channels)}}
      data = StandardizeChannels(opts)(data)
      assert data["samples"]["audio"].shape == (N, T, out_channels)
  
file_path: ml-cvnets/tests/transforms/test_audio.py
imports: import copy
  import os
  import shutil
  import tempfile
  import pytest
  import scipy.io.wavfile
  import torch
  from data.transforms.audio import AudioResample, Gain, LambdaAudio, MFCCs, Noise, Roll, SetFixedLength, StandardizeChannels
  from tests.configs import get_config
label_desc: Use image node_id 6 for calling a global function with example usage: test_standardize_channels(in_channels, out_channels) without return types